Pramod Kaushik Mudrakarta

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 2 papers; trusts 204 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 41 citations into it; #19,107 of 21,575 by trust here, #9,872 by citations
• Artificial Intelligence — 40 citations into it; #30,732 of 35,345 by trust here, #14,438 by citations
• Natural Language Processing — 14 citations into it; #5,005 of 5,688 by trust here, #3,529 by citations
• Safety, Robustness & Interpretability — 9 citations into it
• Model Architectures — 7 citations into it
• Efficiency & Compression — 6 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Pramod Kaushik Mudrakarta trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Christian Szegedy
5. Andrew Zisserman
6. Yoshua Bengio
7. Kaiming He
8. Diederik P. Kingma
9. Jia Deng
10. Yann LeCun

Who trusts Pramod Kaushik Mudrakarta overall

1. Mengnan Du
2. Frederick Liu
3. Han Cai
4. Varun Manjunatha
5. Aliaksandra Shysheya
6. Sahaj Garg
7. Zhuosheng Zhang
8. Ninghao Liu
9. Chuang Gan
10. Besim Avci

Papers from Pramod Kaushik Mudrakarta's perspective

Ordered by how strongly the researchers Pramod Kaushik Mudrakarta trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• K For The Price Of 1: Parameter Efficient Multi-task And Transfer Learning (2018) — 76 citations
• Did the Model Understand the Question? (2018) — 206 citations